Rough-Set Multiple-Criteria ABC Analysis

  • Ye Chen
  • Kevin W. Li
  • Jason Levy
  • Keith W. Hipel
  • D. Marc Kilgour
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4259)


Multiple-criteria ABC (MCABC) analysis is conducted using a dominance-based rough set approach. ABC analysis, a well-known technique for inventory planning and control, divides stock-keeping units (SKUs) into three classes according to annual dollar usage. But MCABC analysis offers more managerial flexibility by including other criteria, such as lead time and criticality, in the classification of SKUs. The objective of this paper is to propose an MCABC method that uses the dominance-based rough set approach to generate linguistic rules that represent a decision-maker’s preferences based on the classification of a test data set. These linguistic rules are then used to classify all SKUs. A case study demonstrates that the procedure is feasible.


Lead Time Analytic Hierarchical Process Linguistic Rule Management Attention Multiple Criterion Decision Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ye Chen
    • 1
  • Kevin W. Li
    • 2
  • Jason Levy
    • 3
  • Keith W. Hipel
    • 1
  • D. Marc Kilgour
    • 4
  1. 1.Department of Systems Design EngineeringUniversity of WaterlooWaterloo, OntarioCanada
  2. 2.Odette School of BusinessUniversity of WindsorWindsor, OntarioCanada
  3. 3.Department of Applied Disaster and Emergency StudiesBrandon UniversityBrandon, ManitobaCanada
  4. 4.Department of MathematicsWilfrid Laurier UniversityWaterloo, OntarioCanada

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